Method for triggering restraining means in a motor vehicle

ABSTRACT

A method for triggering a restraining device in a motor vehicle is proposed, where a crash severity and an occupant categorization are implemented independently of each other. By linking the crash severity with the occupant categorization, the restraining device required for the vehicle occupants is triggered. The crash severity is subdivided in accordance with the triggering events frontal impact, side impact, rear impact or vehicle roll-over. A decisive advantage is that the crash severity is implemented independently of the occupant categorization.

BACKGROUND INFORMATION

[0001] The present invention is based on a method for triggeringrestraining means in a motor vehicle according to the definition of thespecies in the independent claim.

[0002] It is already known to use vehicle sensors, such as accelerationsensors, to detect a crash by comparing sensor signals from theseacceleration sensors to predefined threshold values. Furthermore, it isknown to use vehicle sensors for occupant categorization in the mannerof a seat mat in a vehicle seat.

SUMMARY OF THE INVENTION

[0003] In contrast, the method according to the present invention fortriggering restraining means in a motor vehicle having the features ofthe independent patent claim has the advantage over the related art thatthe sensor signals are used to determine a crash severity, in thismanner allowing a better activation of the required restraining means,which, if appropriate, are able to be switched in stages or in acontinuous manner. This means that the restraining means are activatedin such a way that an optimal protection is obtained in view of thedetermined crash severity.

[0004] Furthermore, it is advantageous that, by combining the detectedcrash severity with the occupant categorization, an optimal use of therestraining means takes place in that the crash severity and theoccupant categorization are interlinked so as to address the requiredrestraining means alone. This makes it possible, on the one hand, todetermine how the person is seated and which classifying features theperson exhibits and, on the other hand, to use a possible crashseverity, the occupant categorization and the crash severity both beingdetermined independently of one another. Thus, in an advantageousmanner, no restraining means will be triggered if such a triggering doesnot protect a person.

[0005] Moreover, it is advantageous that this also makes it possible totake time sequences into consideration in the deployment of restrainingmeans in that, for instance, it is detected with the aid of the sensorsignals when a second stage of an airbag must be fired in order toobtain maximum protection.

[0006] Due to the separation of the crash-severity detection from theoccupant categorization, the method according to the present inventionallows a modular and structured set-up of the required algorithms. Thecrash-severity detection and the occupant categorization are keptseparate from one another until they are ultimately linked to oneanother to address the required restraining means. In this way, the lackof, for instance, data from a sensor will have an effect only when thecrash-severity detection and the occupant categorization are linked. Itis then possible to trigger, in a more or less adapted manner, therestraining means as a function of the quality of the crash-severitydetection and the occupant categorization.

[0007] Advantageous improvements of the method of triggering restrainingmeans in a motor vehicle, indicated in the independent claim, arerendered possible by measures and further refinements specified in thedependent claims.

[0008] It is particularly advantageous that the first sensor signals,which are used to determine the crash severity, record operatingdynamics data, a vehicle intrusion and ambient environment data of thevehicle. Here, operating dynamics data are accelerations of the linearand circular type, so that brake processes and roll-over processes arethereby recorded as well. Intrusion means that a foreign object collideswith the vehicle, possibly indenting the passenger cabin, and aso-called intrusion thereby takes place. A respective example is apressure sensor accommodated in a side panel of a motor vehicle todetect the air compression in the side panel in the event of acollision. Ambient environment data of the vehicle are detected by imagesensors, ultrasound or, for example, radar, so as to detect objectscolliding with the vehicle as early as possible prior to the collisionand to still prevent such a potential collision. These sensor dataprovide comprehensive information about the vehicle as well as theenvironment and especially collision data, which result in acrash-severity determination and estimation. It is also possible toassign crash-severity data to each of the individual triggering events,which are then entered into the linkage with the categorization ofvehicle occupants. A crash may consist of a combination of thetriggering events.

[0009] Moreover, it is advantageous that with the aid of additionalsensor signals the weight, the seating position and the use of a seatbelt are utilized for the purpose of occupant categorization. On thisbasis, a comprehensive concept of the respective occupant may beobtained on the basis of which a complete categorization may beimplemented. For instance, persons may be subdivided into threedifferent categories. For one, there is the child which is not to beprotected by an airbag so as to avoid an injury caused by the airbag;there is a women weighing 100 lbs who is able to be protected by anairbag with a weak pressure increase without being injured; and thereare the other persons who are protectable by an airbag-stage having ahigher pressure increase without risking injury to themselves, sincethey are usually further away from an airbag module. An example of asensor to be used here are pressure-dependent resistance elements in aseat mat of a respective vehicle seat, by which it is possible togenerate seat profiles from which the weight of the respective person,the seat occupancy and also the seating position may be inferred.However, optical or ultrasound sensors may be used as well. By utilizingan additional appropriate sensory system it is possible to ascertainwhether or not a seat belt was used.

[0010] Furthermore, it is advantageous that a device is provided whichincludes the requisite means for implementing the method describedabove.

BRIEF DESCRIPTION OF THE DRAWING

[0011] Exemplary embodiments of the present invention are shown in thedrawing and are explained in greater detail in the followingdescription.

[0012] The figures show:

[0013]FIG. 1 a flow chart of the method according to the presentinvention;

[0014]FIG. 2 a block diagram of the device according to the presentinvention;

[0015]FIG. 3 a block diagram of the preprocessing of sensor signals; and

[0016]FIG. 4 a triggering matrix for activating the restraining means.

[0017] Specification

[0018] Due to the increasing use of a growing number of airbags in amotor vehicle, it is necessary to activate these airbags in the mostappropriate manner in a given situation. Even the fact that airbags areable to be fired in stages means that this degree of freedom in theactivation should be implemented as a function of the crash situationand the respective vehicle occupants, this situation being determined ineach case by a possible crash severity and the individual occupants. Afrontal or side collision constitutes a potentially greater crashseverity for an occupant than a rear collision. On the basis of theweight of the person, appropriate restraining forces may be exerted onthe person, especially given multi-stage airbags, so as to ensureoptimum protection, without the occupant being injured by therestraining means.

[0019] According to the present invention, a method for triggeringrestraining means in a motor vehicle, therefore, is employed in whichthe crash severity and the occupant categorization are implementedindependently of one another. This ensures that no retrospective effector fault propagation occurs when the two parameters are determined, dueto a faulty or missing sensor value. Linking the crash severity to theoccupant categorization allows an individual activation of therespective restraining means. This also means that this linkage permitsan activation as a function of time when multi-stage airbags are used.

[0020] In FIG. 1, the method of the present invention for triggering ofrestraining means in a motor vehicle is represented as a flow chart. Ina first step, various sensor signals are recorded and digitized. In thiscase, acceleration sensors, engine speed sensors, radar sensors,ultrasound sensors and a side-impact sensory system such as pressuresensors are used, which are distributed over the vehicle and may also belocated in the control device of the restraining means. The methodaccording to the present invention is implemented in the control device.

[0021] However, many other sensor principles suitable to detect theseverity of a crash may be used. In this context, the vehicle sensorsmust detect one of the four events, such as frontal impact, side impact,rear impact or roll-over, or at least make these detectable by combiningthe sensor signals.

[0022] In method step 2, the control device of the restraining meansdetermines the crash severity from these sensor signals. Specialcategorization approaches, or the exceeding of dynamic and staticthreshold values, may be used in the consideration of the exceedingtime.

[0023] The sensor signals in each case are evaluated via a separatesignal preprocessing and then assigned to one of the four triggeringevents mentioned above on the basis of the detected characteristics. Theassignment is linked to a signal linkage, which results in adetermination of the respective crash severity. Depending on thecapability of the used sensory system, the crash severity may be carriedout to varying grades and resolutions.

[0024] The classification of a crash severity may be implemented on thebasis of a feature analysis. For instance, using the wavelettransformation on crash-acceleration signals provides informationregarding the maximum signal energies and average signal energies indifferent frequency bands of the signal. These then constitutecharacteristic data for the individual crash types, and, when combined,may be used to classify or detect a crash severity. For each frequencyband, two features are then at hand. The individual crash types maysubsequently be identified on the basis of these features. Crashes maybe divided into types, each crash type having a set of features. Thefeatures detected by a vehicle sensor are compared to these storedfeatures, differences being formed between the detected and the storedfeatures. Therefore, energy differences are ascertained. Thesedifferences must be below a predefined threshold value in order toidentify a crash type and, thus, the crash severity. That is, all thefeatures of a set for a crash must show a difference that is below thisfirst threshold value. Only then will it be possible to identify therespective crash type. The crash types are structured such that anidentification will always be possible, at least one crash type alsorepresenting a non-trigger. These are crash types that do not entail atriggering of the restraining means.

[0025]FIG. 3 shows a block diagram of the signal-preprocessing ofacceleration signals. Acceleration signals from remote accelerationsensors, that is, acceleration sensors located outside of the controldevice of the restraint system, are received at inputs 17 and 20, to beintegrated in each case in integrators 18 and 19. A crash type orcrash-severity information of this sensor is determined with the aid ofthe integrated signal in block 21. This crash type may be subdivided onthe basis of the integrated signal, for instance by a predefined delaytime and the gradient. The detected crash type is then forwarded toblock 25, which determines the crash severity, for which it also usesthe signal that is applied to signal input 23. This signal is anacceleration signal generated in the control device by a sensor locatedtherein. It is also possible to use two acceleration sensors here, whichare positioned perpendicularly to each other, so as to detect theaccelerations in the direction of travel and in the lateral direction.

[0026] This signal is likewise integrated in block 24, then to beassigned in block 22 to a crash severity on the basis of itscharacteristic curve. To obtain the crash severity, a comparison of theintegral to a threshold formed from the acceleration signals isimplemented. However, other approaches for classifying signals areconceivable as well. This crash severity is then transmitted to a seconddata input of block 25, which implements a merged crash-severityclassification from these two crash-severity classifications. In thisway, different sensors, sensing signals independently of one another,are linked with respect to their signals as well as the ensuing results,in order to determine the overall crash severity. The crash severity isthen available as a value between zero and one or between zero and onehundred percent. On this basis, the severity of a crash is estimated. Inparticular, it is also possible here that in a crash both a frontalimpact and a side impact are each assigned a particular crash severityat the same time.

[0027] In FIG. 1, the occupant categorization is implemented in methodstep 3, which runs in parallel to method step 2. Here, the occupantcategorization is implemented using a seat mat which is located in arespective vehicle seat. The seat mat is provided withpressure-responsive resistors which generate a seat profile of theperson or the object occupying the vehicle seat. This seat profile iscalculated and evaluated by a control unit assigned to the seat mat. Theweight, the seating position and the use of a seat belt, whosedeployment is registered by an additional sensor, are taken into accounthere. The position determination is particularly important with respectto the area taken up by the inflated airbag. If an occupant is presentin this area, which is also referred to as keep-out-zone, when theairbag is inflated, a contact with the rapidly unfolding airbag takesplace. This may result in considerable injuries, so that an airbaginflation should be avoided in these cases under all circumstances. Thismonitoring may be implemented in a static or dynamic manner.

[0028] In FIG. 1, in method step 4, an injury danger is determined basedon the crash severity and the occupant categorization. This injurydanger is realized here via a matrix for activating the restrainingmeans. FIG. 4 shows such a matrix. In a left column, the potentialtriggering events, side impact 27 and frontal impact 28, are stored,these crash events being weighted here with a percentage expressing thecrash severity. The other accident or triggering events may be added aswell so as to be integrated in the linkage.

[0029] In the upper line, in fields 29, 30, 31, 32 and 33, theoccupant-categorization features, namely use of belt 29, passengerweight 30, seating position 31, offset to front 32 and lateral offset33, are represented. In gate 34, lateral offset 33, the crash severityof side impact 27 and the result of an additional linkage are linked toeach other to activate, if appropriate, a window bag or inflatablecurtain, which is represented by field 41. A window bag or an inflatablecurtain is an airbag which unfolds from the vehicle ceiling above theside window or the B-column to provide protection between a vehicleoccupant and side part of the vehicle.

[0030] The information regarding the use of a belt 29, the weight of therespective person 30 and the crash severity with respect to a frontalcollision 28 are linked to each other in gate 35 in order to possiblytrigger the front airbag, for instance in the steering wheel. Inaddition to being connected to gate 34, gate 35, via its data output, isalso connected to timing element 36. Timing element 36 delays the signalby a predefined value to then trigger the second stage of front airbag39. Weight 30 is also directly forwarded to timing element 36, so thatboth the first and also the second airbag stage are able to be triggeredin accordance with the predefined value.

[0031] The linkages are based on previous simulations and tests, withfuzzy logic concepts being especially applicable here. The linking ingates 34 and 35 is then implemented on the basis of this informationregarding the effects of a crash severity on an occupant. Tables arethen available in the control device, which, depending on the signalsthat are available at the inputs of gates 34 and 35, specify theassignment and activation of the restraining means. In the simplestcase, this may be done by logical linkings. Additional linkings arepossible.

[0032] In method step 6, the activation of the required restrainingmeans, which were determined by the triggering matrix, is finallyimplemented.

[0033]FIG. 2 shows the device according to the present invention forimplementing the method in the form of a block diagram. An accelerationsensor 7, an occupant categorization (seat mat) 8, an environment sensor9 and an engine speed sensor 10 are shown by way of illustration hereand are able to be connected to an interface 11 of an airbag controldevice. It is possible to include a multitude of additional sensors,which then leads to a finer activation of the required restrainingmeans. Interface unit 11 forms a multiplex from the sensor signals,which is evaluated by processor 12 connected to the data output ofinterface element 11. Processor 11 implements the afore-describedmethod, i.e., determines the crash severity, the occupant categorizationand its linking, in order to then activate the respective restrainingmeans 14, 15, 16 via activation means 13, in a manner that isappropriate for the situation.

What is claimed is:
 1. A method for triggering restraining means in amotor vehicle, a crash being detected as a function of first sensorsignals from first vehicle sensors (7, 9, 10), a categorization ofvehicle occupants being implemented on the basis of second sensorsignals from second vehicle sensors (8); a crash severity beingdetermined on the basis of at least one of the triggering events frontalimpact, side impact, rear impact or vehicle roll-over recognized withthe aid of the first sensor signals; and the categorization of thevehicle occupants and the crash severity being linked to each other fortriggering the restraining means required for the vehicle occupants,wherein the crash severity is additionally determined as a function of acrash type, which is ascertained on the basis of features extracted fromthe first signals.
 2. The method as recited in claim 1, whereinoperating dynamics data and/or intrusion data and/or environment data ofthe vehicle are ascertained from the first sensor signals to determinethe triggering events.
 3. The method as recited in claim 1 or 2, whereincrash severity data are determined for each of the individual triggeringevents, the crash severity data then being linked with thecategorization of the vehicle occupants.
 4. The method as recited inclaim 1, 2 or 3, wherein the weight of a specific vehicle occupant, therespective seating position and the use of a respective vehicle beltcoming from the second sensor signals is used to categorize the vehicleoccupants.
 5. A device for implementing the method as recited in one ofclaims 1 through 4, wherein the device a processor (12), whichdetermines the crash severity and implements the categorization of thevehicle occupants on the basis of the first and second sensor signalsand accordingly trigger the restraining means (14-16), the processor(12) being able to be connected to the first and second vehicle sensors(7-10) in the motor vehicle; the processor (12) linking the crashseverity and the categorization of the vehicle occupants in order toactivate the subsequently required restraining means (14-16); and theprocessor (12) additionally determining the crash severity as a functionof a crash type which the processor (12) ascertains on the basis of thefeatures extracted from the first signals.
 6. The device as recited inclaim 5, wherein the first vehicle sensors (7, 9, 10) acquire thevehicle dynamics data and/or the intrusion data and/or the environmentdata of the vehicle in order to determine the crash severity in thevehicle, and the second vehicle sensors (8) acquire the weight and theseating position of the respective vehicle occupant and the use of therespective vehicle belt in order to categorize the vehicle occupants.